Session

DescriptionScientific workflows have underpinned some of the most significant discoveries of the past several decades. Workflow management systems (WMS) provide abstraction and automation that enable researchers to easily define sophisticated computational processes, and to then execute them efficiently on parallel and distributed computing systems. As workflows have been adopted by multiple scientific communities, they are becoming more complex and require more sophisticated workflow management capabilities. This workshop focuses on the many facets of scientific workflow composition, management, sustainability, and application to domain sciences in an increasingly diverse landscape. The workshop covers a broad range of topics in the scientific workflow lifecycle that include: reproducible research with workflows; workflow execution in distributed and heterogeneous environments; application of AI/ML in workflow management; workflow provenance; serverless workflows; exascale computing with workflows; stream-processing, interactive, adaptive and data-driven workflows; workflow scheduling and resource management; workflow fault-tolerance, debugging, performance analysis/modeling; big data and AI workflows, etc.